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Home»TRIZ Case»Predicting Plasma Layer Thickness with Circuit Modeling

Predicting Plasma Layer Thickness with Circuit Modeling

May 22, 20263 Mins Read
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Predicting Plasma Layer Thickness with Circuit Modeling

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Summary

Problems

Existing plasma enhanced chemical vapor deposition (PECVD) processes face challenges in predicting the structure of deposited layers, particularly selectivity with respect to underlying materials, which is crucial for minimizing feature size and resistance in semiconductor devices.

Innovation solutions

A plasma layer deposition apparatus and method that utilizes an equivalent circuit model to predict the selectivity of layer thickness by determining sheath voltage based on a correlation with pre-stored selectivity values, using a plasma layer deposition apparatus with components like a substrate stage, electrodes, and an impedance matcher to simulate the deposition process.

TRIZ Analysis

Specific contradictions:

layer structure prediction accuracy
vs
experimental time

General conflict description:

Manufacturing precision
vs
Loss of time
TRIZ inspiration library
10 Preliminary action
Try to solve problems with it

Principle concept:

If PECVD process is used for layer deposition, then deposition quality can be achieved, but trial and error methods are required to predict layer structure and selectivity

Why choose this principle:

The patent applies preliminary action by developing an equivalent circuit model that can predict layer thickness profile and selectivity before actual deposition experiments are conducted. The model uses electrical parameters (impedance, voltage, current) to calculate deposition characteristics in advance, eliminating the need for iterative trial-and-error experimentation.

TRIZ inspiration library
28 Mechanics substitution (Replace mechanical system)
Try to solve problems with it

Principle concept:

If PECVD process is used for layer deposition, then deposition quality can be achieved, but trial and error methods are required to predict layer structure and selectivity

Why choose this principle:

The patent replaces the traditional mechanical/experimental approach of measuring layer thickness through physical deposition and measurement with an electrical modeling approach. By substituting the physical deposition process with an equivalent circuit model that uses electrical measurements and calculations, the system can predict deposition outcomes without actual material deposition.

Application Domain

plasma deposition layer thickness prediction semiconductor optimization

Data Source

Patent US20250266244A1 Plasma layer deposition apparatus and method of predicting thickness profile of layer
Publication Date: 21 Aug 2025 TRIZ 电器元件
FIG 01
US20250266244A1-D00001
FIG 02
US20250266244A1-D00002
FIG 03
US20250266244A1-D00003
Login to view Image

AI summary:

A plasma layer deposition apparatus and method that utilizes an equivalent circuit model to predict the selectivity of layer thickness by determining sheath voltage based on a correlation with pre-stored selectivity values, using a plasma layer deposition apparatus with components like a substrate stage, electrodes, and an impedance matcher to simulate the deposition process.

Abstract

A method of predicting a thickness profile of a layer includes providing a plasma layer deposition apparatus, loading a wafer on a substrate stage, where the wafer includes a first region having a first material and a second region having a second material, deriving an equivalent circuit model of a plasma system simulating the plasma layer deposition apparatus, determining a sheath voltage based on the equivalent circuit model, the sheath voltage corresponding to a voltage applied to a space adjacent to the wafer by a matcher current from an impedance matcher, and predicting a selectivity of the layer as a ratio between a first thickness of a first deposition portion on the first region and a second thickness of a second deposition portion on the second region based on a correlation between the determined sheath voltage and a pre-stored selectivity value.

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    layer thickness prediction plasma deposition semiconductor optimization
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    Table of Contents
    • Predicting Plasma Layer Thickness with Circuit Modeling
      • Summary
      • TRIZ Analysis
      • Data Source
      • Accelerate from idea to impact
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